def test_prognostic_composite_two_components_incompatible_input_dims():
prognostic1 = MockTendencyComponent(
input_properties={
'input1': {
'dims': ['dims1', 'dims2'],
'units': 'degK',
},
},
diagnostic_properties={},
tendency_properties={},
diagnostic_output={},
tendency_output={},
)
prognostic2 = MockTendencyComponent(
input_properties={
'input1': {
'dims': ['dims1', 'dims3'],
'units': 'degK',
},
},
diagnostic_properties={},
tendency_properties={},
diagnostic_output={},
tendency_output={},
)
try:
TendencyComponentComposite(prognostic1, prognostic2)
except InvalidPropertyDictError:
pass
else:
raise AssertionError('Should have raised InvalidPropertyDictError')
def test_prognostic_composite_two_components_overlapping_diagnostic():
prognostic1 = MockTendencyComponent(
input_properties={},
diagnostic_properties={'diag1': {
'dims': ['dim1'],
'units': 'm',
}},
tendency_properties={},
diagnostic_output={},
tendency_output={},
)
prognostic2 = MockTendencyComponent(
input_properties={},
diagnostic_properties={'diag1': {
'dims': ['dim1'],
'units': 'm',
}},
tendency_properties={},
diagnostic_output={},
tendency_output={},
)
try:
TendencyComponentComposite(prognostic1, prognostic2)
except SharedKeyError:
pass
else:
raise AssertionError('Should have raised SharedKeyError')
def test_prognostic_composite_two_components_swapped_input_dims():
prognostic1 = MockTendencyComponent(
input_properties={
'input1': {
'dims': ['dims1', 'dims2'],
'units': 'degK',
},
},
diagnostic_properties={},
tendency_properties={},
diagnostic_output={},
tendency_output={},
)
prognostic2 = MockTendencyComponent(
input_properties={
'input1': {
'dims': ['dims2', 'dims1'],
'units': 'degK',
},
},
diagnostic_properties={},
tendency_properties={},
diagnostic_output={},
tendency_output={},
)
composite = TendencyComponentComposite(prognostic1, prognostic2)
diagnostic_properties = {}
tendency_properties = {}
assert (composite.input_properties == prognostic1.input_properties
or composite.input_properties == prognostic2.input_properties)
assert composite.diagnostic_properties == diagnostic_properties
assert composite.tendency_properties == tendency_properties
def test_prognostic_composite_two_components_tendency_compatible_units():
prognostic1 = MockTendencyComponent(
input_properties={},
diagnostic_properties={},
tendency_properties={'tend1': {
'dims': ['dim1'],
'units': 'km/s',
}},
diagnostic_output={},
tendency_output={},
)
prognostic2 = MockTendencyComponent(
input_properties={},
diagnostic_properties={},
tendency_properties={
'tend1': {
'dims': ['dim1'],
'units': 'm/day'
},
},
diagnostic_output={},
tendency_output={},
)
composite = TendencyComponentComposite(prognostic1, prognostic2)
assert 'tend1' in composite.tendency_properties.keys()
assert composite.tendency_properties['tend1']['dims'] == ['dim1']
assert units_are_compatible(
composite.tendency_properties['tend1']['units'], 'm/s')
def test_prognostic_composite_two_components_compatible_input_units():
prognostic1 = MockTendencyComponent(
input_properties={
'input1': {
'dims': ['dims1', 'dims2'],
'units': 'km',
},
},
diagnostic_properties={},
tendency_properties={},
diagnostic_output={},
tendency_output={},
)
prognostic2 = MockTendencyComponent(
input_properties={
'input1': {
'dims': ['dims1', 'dims2'],
'units': 'cm',
},
},
diagnostic_properties={},
tendency_properties={},
diagnostic_output={},
tendency_output={},
)
composite = TendencyComponentComposite(prognostic1, prognostic2)
assert 'input1' in composite.input_properties.keys()
assert composite.input_properties['input1']['dims'] == ['dims1', 'dims2']
assert units_are_compatible(composite.input_properties['input1']['units'],
'm')
def test_empty_prognostic_composite():
prognostic_composite = TendencyComponentComposite()
state = {'air_temperature': 273.15}
tendencies, diagnostics = prognostic_composite(state)
assert len(tendencies) == 0
assert len(diagnostics) == 0
assert isinstance(tendencies, dict)
assert isinstance(diagnostics, dict)
def test_prognostic_composite_cannot_use_diagnostic():
try:
TendencyComponentComposite(MockEmptyDiagnosticComponent())
except TypeError:
pass
except Exception as err:
raise err
else:
raise AssertionError('TypeError should have been raised')
def test_prognostic_composite_calls_one_prognostic(mock_call):
mock_call.return_value = ({'air_temperature': 0.5}, {'foo': 50.})
prognostic_composite = TendencyComponentComposite(
MockEmptyTendencyComponent())
state = {'air_temperature': 273.15}
tendencies, diagnostics = prognostic_composite(state)
assert mock_call.called
assert tendencies == {'air_temperature': 0.5}
assert diagnostics == {'foo': 50.}
def test_prognostic_composite_calls_two_prognostics(mock_call):
mock_call.return_value = ({'air_temperature': 0.5}, {})
prognostic_composite = TendencyComponentComposite(
MockEmptyTendencyComponent(), MockEmptyTendencyComponent())
state = {'air_temperature': 273.15}
tendencies, diagnostics = prognostic_composite(state)
assert mock_call.called
assert mock_call.call_count == 2
assert tendencies == {'air_temperature': 1.}
assert diagnostics == {}
def test_prognostic_composite_two_components_input():
prognostic1 = MockTendencyComponent(
input_properties={
'input1': {
'dims': ['dims1', 'dims2'],
'units': 'degK',
},
'input2': {
'dims': ['dims1'],
'units': 'm',
},
},
diagnostic_properties={},
tendency_properties={},
diagnostic_output={},
tendency_output={},
)
prognostic2 = MockTendencyComponent(
input_properties={
'input1': {
'dims': ['dims1', 'dims2'],
'units': 'degK',
},
'input3': {
'dims': ['dims2'],
'units': '',
},
},
diagnostic_properties={},
tendency_properties={},
diagnostic_output={},
tendency_output={},
)
composite = TendencyComponentComposite(prognostic1, prognostic2)
input_properties = {
'input1': {
'dims': ['dims1', 'dims2'],
'units': 'degK',
},
'input2': {
'dims': ['dims1'],
'units': 'm',
},
'input3': {
'dims': ['dims2'],
'units': '',
},
}
diagnostic_properties = {}
tendency_properties = {}
assert composite.input_properties == input_properties
assert composite.diagnostic_properties == diagnostic_properties
assert composite.tendency_properties == tendency_properties
def test_prognostic_composite_single_diagnostic():
prognostic = MockTendencyComponent(
input_properties={},
diagnostic_properties={'diag1': {
'dims': ['dims2'],
'units': '',
}},
tendency_properties={},
diagnostic_output={},
tendency_output={},
)
composite = TendencyComponentComposite(prognostic)
assert composite.input_properties == prognostic.input_properties
assert composite.diagnostic_properties == prognostic.diagnostic_properties
assert composite.tendency_properties == prognostic.tendency_properties
def test_prognostic_component_handles_units_when_combining(
mock_call, mock2_call):
mock_call.return_value = ({
'eastward_wind':
DataArray(1., attrs={'units': 'm/s'})
}, {})
mock2_call.return_value = ({
'eastward_wind':
DataArray(50., attrs={'units': 'cm/s'})
}, {})
prognostic1 = MockEmptyTendencyComponent()
prognostic2 = MockEmptyTendencyComponent2()
composite = TendencyComponentComposite(prognostic1, prognostic2)
tendencies, diagnostics = composite({})
assert tendencies['eastward_wind'].to_units('m/s').values.item() == 1.5
def test_two_prognostic_composite_compatible_dims():
prognostic = MockTendencyComponent(
input_properties={
'input1': {
'dims': ['dims1', 'dims2'],
'units': 'degK',
},
'input2': {
'dims': ['dims1', 'dims2'],
'units': 'degK'
}
},
diagnostic_properties={},
tendency_properties={
'tend1': {
'dims': ['dims1', 'dims2'],
'units': 'degK / day',
}
},
diagnostic_output={},
tendency_output={},
)
prognostic2 = MockTendencyComponent(
input_properties={
'input1': {
'dims': ['dims1', 'dims2'],
'units': 'degK',
},
'input2': {
'dims': ['dims1', 'dims2'],
'units': 'degK'
}
},
diagnostic_properties={},
tendency_properties={
'tend1': {
'dims': ['dims1', 'dims2'],
'units': 'degK / day',
}
},
diagnostic_output={},
tendency_output={},
)
composite = TendencyComponentComposite(prognostic, prognostic2)
assert composite.input_properties == prognostic.input_properties
assert composite.diagnostic_properties == prognostic.diagnostic_properties
assert composite.tendency_properties == prognostic.tendency_properties
def test_prognostic_composite_two_components_tendency():
prognostic1 = MockTendencyComponent(
input_properties={},
diagnostic_properties={},
tendency_properties={'tend1': {
'dims': ['dim1'],
'units': 'm/s',
}},
diagnostic_output={},
tendency_output={},
)
prognostic2 = MockTendencyComponent(
input_properties={},
diagnostic_properties={},
tendency_properties={
'tend1': {
'dims': ['dim1'],
'units': 'm/s'
},
'tend2': {
'dims': ['dim1'],
'units': 'degK/s'
}
},
diagnostic_output={},
tendency_output={},
)
composite = TendencyComponentComposite(prognostic1, prognostic2)
input_properties = {}
diagnostic_properties = {}
tendency_properties = {
'tend1': {
'dims': ['dim1'],
'units': 'm/s'
},
'tend2': {
'dims': ['dim1'],
'units': 'degK/s'
}
}
assert composite.input_properties == input_properties
assert composite.diagnostic_properties == diagnostic_properties
assert composite.tendency_properties == tendency_properties
def test_prognostic_composite_explicit_dims_not_in_input():
prognostic = MockTendencyComponent(
input_properties={
'input1': {
'dims': ['dims1', 'dims2'],
'units': 'degK',
}
},
diagnostic_properties={},
tendency_properties={
'tend1': {
'dims': ['dims1', 'dims2'],
'units': 'degK / day',
}
},
diagnostic_output={},
tendency_output={},
)
composite = TendencyComponentComposite(prognostic)
assert composite.input_properties == prognostic.input_properties
assert composite.diagnostic_properties == prognostic.diagnostic_properties
assert composite.tendency_properties == prognostic.tendency_properties
def test_prognostic_composite_two_components_diagnostic():
prognostic1 = MockTendencyComponent(
input_properties={},
diagnostic_properties={'diag1': {
'dims': ['dim1'],
'units': 'm',
}},
tendency_properties={},
diagnostic_output={},
tendency_output={},
)
prognostic2 = MockTendencyComponent(
input_properties={},
diagnostic_properties={'diag2': {
'dims': ['dim2'],
'units': 'm',
}},
tendency_properties={},
diagnostic_output={},
tendency_output={},
)
composite = TendencyComponentComposite(prognostic1, prognostic2)
input_properties = {}
diagnostic_properties = {
'diag1': {
'dims': ['dim1'],
'units': 'm',
},
'diag2': {
'dims': ['dim2'],
'units': 'm',
},
}
tendency_properties = {}
assert composite.input_properties == input_properties
assert composite.diagnostic_properties == diagnostic_properties
assert composite.tendency_properties == tendency_properties